Three dimensional medical scans of patients, such as CT (computed tomography), MR (magnetic resonance), US (ultra sound), or PET (positron emission tomography), produce a series of two dimensional (2D) image slices that together make up 3D images. The two dimensional image slices can be stored to create a set of primary or target images. A medical professional may take another set of images of the patient that can be stored in memory to create a set of secondary or source images. These secondary or source images may be compared with the primary or target images, for example, and processed through an image registration to define a point to point correlation between the primary and the secondary images. However, image registrations, particularly high order registrations including deformable registrations, of any volume may be difficult to interpret and evaluate for accuracy, and doing so can be time consuming for medical professionals.
The aforementioned difficulty in understanding and evaluation of registrations is not ideal. Accordingly, a new system and method is desired.